Associate II - Data Science

General Position Information

• Reports directly to (Title): Manager, Advanced Analytics and Data Science
• Matrix reports to (Title): As applicable based on HR Transformation Analytics portfolio alignment
• Direct Reports: Individual Contributor
• Created / Last Revised: -

Position Summary

The Data Scientist supports the Human Resources Group by applying statistical analysis, machine learning, experimentation, forecasting, and advanced analytics techniques to workforce and HR business problems. This role partners with HR leaders, data engineers, data analysts, business insights analysts, product teams, and governance partners to develop explainable, ethical, and actionable analytical solutions.

The role is responsible for framing analytical problems, preparing data, feature engineering, building and evaluating models, communicating findings, and supporting responsible deployment of predictive or AI-enabled insights. Success requires statistical rigor, business context, coding capability, responsible AI awareness, and clear communication.

Responsibilities

Advanced Analytics Modeling

• Develop statistical, predictive, forecasting, segmentation, classification, natural language, or machine learning analyses for HR and workforce use cases.
• Prepare features, evaluate model performance, document assumptions, and compare modeling approaches based on business needs and data quality.
• Support experiments, pilots, model validations, and analytical prototypes that inform HR decisions and transformation priorities.

Responsible AI, Evaluation Documentation

• Document model purpose, data sources, assumptions, limitations, performance metrics, risks, and appropriate use cases.
• Support fairness, bias, explainability, privacy, and governance reviews for models or AI-enabled analytical outputs.
• Validate results with business stakeholders and avoid unsupported or overly deterministic interpretations of workforce data.

Insight Translation Partnership

• Partner with HR domain experts, product analysts, business insights analysts, and data teams to frame problems and interpret results in context.
• Translate advanced analytical findings into practical recommendations, decision options, and measurable next steps.
• Support operationalization of models, model monitoring, and feedback loops in partnership with engineering and governance teams.

AI-Augmented Data Science

• Use approved AI tools to support code drafting, exploratory analysis, feature brainstorming, documentation, model comparison summaries, and research synthesis.
• Validate AI-assisted code, findings, and modeling recommendations through reproducible methods and peer review.
• Identify opportunities where AI, machine learning, or natural language analytics can responsibly improve HR insight and decision support.

AI Preparedness Expectations

• Uses AI to accelerate code drafts, research synthesis, feature exploration, and documentation while preserving reproducibility and validation.
• Understands AI risk, model limitations, fairness, explainability, privacy, and appropriate human oversight for workforce-related models.
• Builds capability in responsible AI, model operations, generative AI evaluation, decision science, and AI-enabled workforce analytics.

Education Experience

• Bachelor's degree in Computer Science, Machine Learning, Data Analytics, Statistics, Engineering, Economics, or a related field; equivalent experience may be considered.
• Typically 1-2 years of experience in a related environment.
• Experience with statistical analysis, machine learning, predictive modeling, forecasting, NLP, experimentation, or advanced analytics projects.
• Experience using Python, R, SQL, or similar tools for data preparation, modeling, evaluation, and visualization.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.